Starjob Dataset designed to train LLMs on JSSP

Dataset Overview

Dataset Name: starjob130k.json Number of Entries: 130,000
Number of Fields: 5

Fields Description

1. num_jobs

   • Type: int64
   • Number of Unique Values: 16

2. num_machines

   • Type: int64
   • Number of Unique Values: 16

3. instruction

   • Type: object
   • Number of Unique Values: 130,000
   • Initial description of the problem detailing the number of jobs and machines involved.

4. input

   • Type: object
   • Number of Unique Values: 130,000
   • Description of the problem in LLM format

5. output

   • Type: object
   • Number of Unique Values: 130,000
   • Solution in LLM format: 130,000

6. matrix

   • Type: object
   • Number of Unique Values: 130,000
   • Input problem OR-Tool makspan and solution in Matrix format

Usage

This dataset can be used for training LLMs for job-shop scheduling problems (JSSP). Each entry provides information about the number of jobs, the number of machines, and other relevant details formatted in natural language.

Setting Up Your Python Environment

Follow these instructions to create a virtual environment and install the necessary libraries.

Step 1: Create a Virtual Environment

python3 -m venv llm_env

Activate the Virtual Environment After creating the virtual environment, activate it using the following command:

On Windows

.\llm_env\Scripts\activate

On macOS and Linux

source llm_env/bin/activate

Install the Required Libraries

pip install -r requirements.txt

Training

Make sure to put dataset.json under data directory

python train_llama_3.py

License

This dataset is licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). For more details, see the license description. The dataset will remain accessible for an extended period.